{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "421421d6",
   "metadata": {},
   "source": [
    "# Align + Drizzle\n",
    "This notebook handles the drizzling and alignment of multiple HST observations. In particular, it reduces IR and UV from WFC3 and ACS, drizzling both to same pixel scale, and aligning the UV frames to the WCS of the IR frames. \n",
    "\n",
    "\n",
    "This notebook contains 6 cells:\n",
    "\n",
    "1. imports and defining main directory where your data is/will be\n",
    "\n",
    "2. define helper functions that help clean up ancillary files\n",
    "\n",
    "3. IR_Drizzler() main IR drizzling function that runs Astrodrizzle + Tweakreg, cleans up astrodrizzle ancillary files\n",
    "\n",
    "4. UV_Drizzler() main UVIS drizzling function that runs Astrodrizzle + Tweakreg (using IR image for aligning, if available), cleans up astrodrizzle ancillary files\n",
    "\n",
    "5. Read in csv file and build list of targets to run\n",
    "    \n",
    "6. Loop over targets and run IR and UV drizzlers \n",
    "\n",
    "Two additional cells at the bottom are (1) for removing ancillary files that are written out by Mac OS systems (sometimes hidden ._ files and directories) to free up space (especially when uploading to online repos) and (2) for running astrodrizzle and tweakreg outside the main function on just one target/exposure\n",
    "\n",
    "\n",
    "\n",
    "    \n",
    "Last ran 2025.10.20 by C. Watson"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cf8d1a4",
   "metadata": {},
   "source": [
    "# Note: This is written in a way such that you can run a catalog of sources to fetch, align, and drizzle all exposures that are found in MAST. This means that you MUST check the outputs of all targets (or at least a good handful) to make sure that the parameters defined in astrodrizzle and tweakreg are appropriate for your data!!!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18ef8d56",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os, shutil, glob, time, stat, gc, csv\n",
    "from pathlib import Path\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from astropy.io import fits\n",
    "from drizzlepac import astrodrizzle, tweakreg, tweakback\n",
    "from drizzlepac.haputils.astrometric_utils import create_astrometric_catalog  \n",
    "\n",
    "\n",
    "# --- CONFIG: set your data root ---\n",
    "## This is the main directory where all your data lives, it may not necessarily be the same directory as this notebook\n",
    "## I currently have my data on an external USB drive but your path may be more like /Users/username/research/... etc. \n",
    "Main_dir = Path('/Volumes/AGEL/HST_data')\n",
    "\n",
    "\n",
    "if not Main_dir.exists():\n",
    "    raise FileNotFoundError(f\"Main_dir not found: {Main_dir}\")\n",
    "\n",
    "\n",
    "## This is the path where this notebook lives\n",
    "HOME_DIR = os.getcwd()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "06e27287",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- Utility Functions for handling and cleaning up files  ---\n",
    "\n",
    "def _fix_perms_and_retry(func, path, exc_info):\n",
    "    \"\"\"Make path writable and retry the failing operation (used by rmtree).\"\"\"\n",
    "    try:\n",
    "        os.chmod(path, stat.S_IWRITE | stat.S_IREAD | stat.S_IEXEC)\n",
    "    except Exception:\n",
    "        pass\n",
    "    try:\n",
    "        func(path)\n",
    "    except Exception:\n",
    "        pass\n",
    "\n",
    "def ensure_cwd_not_inside(target: Path):\n",
    "    \"\"\"If CWD is target or a child, cd to its parent so we can delete target.\"\"\"\n",
    "    try:\n",
    "        if Path.cwd().resolve().is_relative_to(target.resolve()):\n",
    "            os.chdir(target.parent.as_posix())\n",
    "    except AttributeError:\n",
    "        # Py<3.9 fallback\n",
    "        cwd = Path.cwd().resolve()\n",
    "        tgt = target.resolve()\n",
    "        try:\n",
    "            cwd.relative_to(tgt)\n",
    "            os.chdir(tgt.parent.as_posix())\n",
    "        except ValueError:\n",
    "            pass\n",
    "\n",
    "def clean_mac_junk_recursive(\n",
    "    root: Path,\n",
    "    delete_cwd_ancillary: bool = True,\n",
    "    ancillary_exts = None\n",
    ") -> int:\n",
    "    \"\"\"Remove AppleDouble/Finder junk under root (rglob).\"\"\"\n",
    "    removed = 0\n",
    "    for patt in (\"**/._*\", \"**/.DS_Store\"):\n",
    "        for p in root.rglob(patt):\n",
    "            try:\n",
    "                p.unlink()\n",
    "                removed += 1\n",
    "            except FileNotFoundError:\n",
    "                pass\n",
    "    # 2) Clean ancillary files in CWD (but NOT if CWD is the reading dir)\n",
    "    if ancillary_exts is None:\n",
    "        ancillary_exts = ['coo', 'png', 'fits', 'match', 'log', 'list']\n",
    "\n",
    "    removed = 0\n",
    "    path = Path(root)\n",
    "    if delete_cwd_ancillary:\n",
    "        cwd = Path(HOME_DIR).resolve()\n",
    "        try:\n",
    "            same_dir = (cwd == path.resolve())\n",
    "        except Exception:\n",
    "            same_dir = False\n",
    "\n",
    "        if not same_dir:\n",
    "            for ext in ancillary_exts:\n",
    "                filelist = glob.glob(\"./*.{}\".format(ext))\n",
    "                for file in filelist:\n",
    "                    try:\n",
    "                        os.remove(file)\n",
    "                        removed += 1\n",
    "                    except FileNotFoundError:\n",
    "                        pass\n",
    "    return removed\n",
    "\n",
    "def safe_rmtree(p: Path, retries: int = 3, delay: float = 0.25):\n",
    "    \"\"\"Robustly remove a directory tree if it exists.\"\"\"\n",
    "    p = Path(p)\n",
    "    # Prevent deleting current working directory (or its parents)\n",
    "    try:\n",
    "        if Path.cwd().resolve().is_relative_to(p.resolve()):\n",
    "            raise RuntimeError(f\"CWD is inside target {p}; refusing to remove\")\n",
    "    except AttributeError:\n",
    "        # Python <3.9 fallback\n",
    "        cwd = Path.cwd().resolve()\n",
    "        try:\n",
    "            cwd.relative_to(p.resolve())\n",
    "            raise RuntimeError(f\"CWD is inside target {p}; refusing to remove\")\n",
    "        except ValueError:\n",
    "            pass\n",
    "\n",
    "    for i in range(retries + 1):\n",
    "        try:\n",
    "            shutil.rmtree(p, onerror=_fix_perms_and_retry)\n",
    "            return\n",
    "        except FileNotFoundError:\n",
    "            return\n",
    "        except OSError:\n",
    "            if i == retries:\n",
    "                raise\n",
    "            time.sleep(delay)\n",
    "\n",
    "\n",
    "def list_fits(dirpath: Path, pattern: str):\n",
    "    \"\"\"Return POSIX-string paths for FITS matching pattern, excluding AppleDouble files.\"\"\"\n",
    "    return [p.as_posix() for p in dirpath.glob(pattern) if not p.name.startswith('._')]\n",
    "\n",
    "def derive_rootname(fpath: str):\n",
    "    \"\"\"Prefer ROOTNAME from FITS header; fallback to filename prefix before first underscore.\"\"\"\n",
    "    try:\n",
    "        return fits.getval(fpath, 'ROOTNAME')\n",
    "    except Exception:\n",
    "        return Path(fpath).name.split('_')[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ea2822b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- IR (WFC3/IR) Drizzler Function ---\n",
    "def IR_Drizzler(object_name, propno, band, camera, pixel_size):\n",
    "    \n",
    "    base = Main_dir\n",
    "    raw_data_dir    = base / f\"{object_name}/HST/{propno}_{band}/raw_data\"\n",
    "    output_data_dir = base / f\"{object_name}/HST/{propno}_{band}\"\n",
    "    ## Create output directorie if needed\n",
    "    output_data_dir.mkdir(exist_ok=True) \n",
    "\n",
    "\n",
    "    temp_dir = output_data_dir / 'temp'\n",
    "    safe_rmtree(temp_dir)\n",
    "    temp_dir.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "    # stage inputs\n",
    "    for src in raw_data_dir.glob('*.fits'):\n",
    "        shutil.copy(src.as_posix(), temp_dir.as_posix())\n",
    "\n",
    "    flt_files = list_fits(temp_dir, '*flt.fits')\n",
    "    if not flt_files:\n",
    "        raise FileNotFoundError(f\"No *flt.fits in {temp_dir}\")\n",
    "\n",
    "    output_prefix = (output_data_dir / f\"{object_name}_{band}_{camera}\").as_posix()\n",
    "\n",
    "\n",
    "    if len(flt_files) < 2:\n",
    "        print(f\"[WARN] Only {len(flt_files)} FLT files found for {object_name} {band}; skipping initial CR rejection.\")\n",
    "        tweakreg.TweakReg((temp_dir / '*flc.fits').as_posix(),\n",
    "                  imagefindcfg={'threshold': 50, 'conv_width': 2.5},\n",
    "                  expand_refcat=True,\n",
    "                  enforce_user_order=False,\n",
    "                  shiftfile=True,\n",
    "                  outshifts=(temp_dir / 'shiftir_flt.txt').as_posix(),\n",
    "                  searchrad=2.0,\n",
    "                  ylimit=0.3,\n",
    "                  updatehdr=False,\n",
    "                  reusename=True,\n",
    "                  wcsname='IR_FLT',\n",
    "                  interactive=False)\n",
    "    else:\n",
    "        # First drizzle (CR rejection)\n",
    "        astrodrizzle.AstroDrizzle(\n",
    "            flt_files,\n",
    "            output=output_prefix,\n",
    "            resetbits=4096,\n",
    "            driz_cr_corr=True,\n",
    "            final_wht_type='EXP',\n",
    "            final_pixfrac=1.0,\n",
    "        )\n",
    "\n",
    "        # TweakReg on CR-cleaned products\n",
    "        tweakreg.TweakReg(\n",
    "            (temp_dir / '*crclean.fits').as_posix(),\n",
    "            imagefindcfg={'threshold': 5, 'conv_width': 3.5, 'dqbits': ~4096},\n",
    "            expand_refcat=True,\n",
    "            enforce_user_order=False,\n",
    "            shiftfile=True,\n",
    "            outshifts=(temp_dir / 'shiftir_flt.txt').as_posix(),\n",
    "            searchrad=2.0,\n",
    "            ylimit=0.3,\n",
    "            updatehdr=True,\n",
    "            reusename=True,\n",
    "            wcsname='IR_FLT',\n",
    "            interactive=False,\n",
    "        )\n",
    "\n",
    "        # Apply updated WCS back to originals\n",
    "        for flt in flt_files:\n",
    "            flid = derive_rootname(flt)\n",
    "            crclean = temp_dir / f\"{flid}_crclean.fits\"\n",
    "            if not crclean.exists():\n",
    "                print(f\"[WARN] Missing {crclean.name}; skipping tweakback for {Path(flt).name}\")\n",
    "                continue\n",
    "            tweakback.tweakback(crclean.as_posix(), input=flt, wcsname='IR_FLT')\n",
    "\n",
    "    # Final drizzle regardless of number of inputs\n",
    "    astrodrizzle.AstroDrizzle(\n",
    "        flt_files,\n",
    "        output=output_prefix,\n",
    "        resetbits=8192,\n",
    "        driz_cr_corr=False,\n",
    "        final_pixfrac=1.0,\n",
    "        final_wcs=True,\n",
    "        final_scale=pixel_size,\n",
    "    )\n",
    "\n",
    "    # Cleanup\n",
    "    gc.collect()                           # close any lingering file handles\n",
    "    clean_mac_junk_recursive(temp_dir)     # remove ._* and .DS_Store everywhere\n",
    "    ensure_cwd_not_inside(temp_dir)        # don't delete our current working dir\n",
    "    time.sleep(0.1)                        # tiny settle for Spotlight/FS\n",
    "    safe_rmtree(temp_dir)                  # delete temp\n",
    "    print(f\"[CLEAN] Removed temp: {temp_dir}\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "afd5e0e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# --- UVIS Drizzler ---\n",
    "def UV_Drizzle(object_name, propno, band, camera, pixel_size):\n",
    "    raw_data_dir    = Main_dir / f\"{object_name}/HST/{propno}_{band}/raw_data\"\n",
    "    output_data_dir = Main_dir / f\"{object_name}/HST/{propno}_{band}\"\n",
    "    ## Create output directorie if needed\n",
    "    output_data_dir.mkdir(exist_ok=True) \n",
    "\n",
    "    temp_dir = output_data_dir / 'temp'\n",
    "    safe_rmtree(temp_dir)\n",
    "    temp_dir.mkdir(parents=True, exist_ok=True)\n",
    "\n",
    "    # stage inputs\n",
    "    for src in raw_data_dir.glob('*.fits'):\n",
    "        shutil.copy(src.as_posix(), temp_dir.as_posix())\n",
    "\n",
    "    flc_files = list_fits(temp_dir, '*flc.fits')\n",
    "    n_files = len(flc_files)\n",
    "    if not flc_files:\n",
    "        raise FileNotFoundError(f\"No *flc.fits in {temp_dir}\")\n",
    "\n",
    "    output_prefix = (output_data_dir / f\"{object_name}_{band}_{camera}\").as_posix()\n",
    "\n",
    "    if n_files < 2:\n",
    "        print(\"Only one exposure: AD with CR rejection; skip tweakreg/tweakback\")\n",
    "        # astrodrizzle.AstroDrizzle(\n",
    "        #     flc_files,\n",
    "        #     output=output_prefix,\n",
    "        #     driz_cr=False,\n",
    "        #     median=False,\n",
    "        #     blot=False,\n",
    "        #     final_wht_type='EXP',\n",
    "        #     final_pixfrac=1.0,\n",
    "        #     final_scale = pixel_size\n",
    "        # )\n",
    "        astrodrizzle.AstroDrizzle(\n",
    "            flc_files,\n",
    "            output=output_prefix,\n",
    "            resetbits=8192,\n",
    "            driz_cr_scale='0.9 0.6', # default '1.2 0.7'\n",
    "            driz_cr_grow=3,\n",
    "            final_wht_type='EXP',\n",
    "            final_pixfrac=1.0,\n",
    "            final_wcs=True,\n",
    "            final_scale=pixel_size\n",
    "        )\n",
    "    else:\n",
    "        astrodrizzle.AstroDrizzle(\n",
    "            flc_files,\n",
    "            output=output_prefix,\n",
    "            resetbits=8192,\n",
    "            driz_cr_corr=True,\n",
    "            driz_cr_scale='0.9 0.6', # default '1.2 0.7'\n",
    "            driz_cr_grow=3,\n",
    "            final_wht_type='EXP',\n",
    "            final_pixfrac=0.8,\n",
    "        )\n",
    "\n",
    "        tweakreg.TweakReg((temp_dir / '*crclean.fits').as_posix(),\n",
    "                  enforce_user_order=False,\n",
    "                  imagefindcfg={'threshold': 20, 'conv_width': 3.5, 'dqbits': ~8192},\n",
    "                  refimagefindcfg={'conv_width': 2.5},\n",
    "                  shiftfile=True,\n",
    "                  outshifts=(temp_dir / 'shiftuv_flt.txt').as_posix(),\n",
    "                  searchrad=5.0,\n",
    "                  ylimit=0.6,\n",
    "                  updatehdr=True,\n",
    "                  wcsname='UVIS_FLC',\n",
    "                  reusename=True,\n",
    "                  interactive=False)\n",
    "\n",
    "        # TweakBack\n",
    "        for flc in flc_files:\n",
    "            flid = derive_rootname(flc)\n",
    "            crclean = temp_dir / f\"{flid}_crclean.fits\"\n",
    "            tweakback.tweakback(crclean.as_posix(), input=flc, wcsname='UVIS_FLC')\n",
    "\n",
    "        # Final drizzle\n",
    "        astrodrizzle.AstroDrizzle(\n",
    "            flc_files,\n",
    "            output=output_prefix,\n",
    "            resetbits=8192,\n",
    "            driz_cr_corr=False,\n",
    "            driz_cr_scale='0.9 0.6', # default '1.2 0.7'\n",
    "            driz_cr_grow=3,\n",
    "            final_pixfrac=1.0,\n",
    "            final_wcs=True,\n",
    "            final_scale=pixel_size,\n",
    "        )\n",
    "\n",
    "\n",
    "    # Cleanup\n",
    "    gc.collect()                           # close any lingering file handles\n",
    "    clean_mac_junk_recursive(temp_dir)     # remove ._* and .DS_Store everywhere\n",
    "    ensure_cwd_not_inside(temp_dir)        # don't delete our current working dir\n",
    "    time.sleep(0.1)                        # tiny settle for Spotlight/FS\n",
    "    safe_rmtree(temp_dir)                  # delete temp\n",
    "    print(f\"[CLEAN] Removed temp: {temp_dir}\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "94a07c02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 61 entries.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "\n",
    "# # --- Build processing list from CSV (same as your notebook) ---\n",
    "proposal_id_no = '17307'\n",
    "filters = ['F606W'] #['F140W', 'F200LP'] \n",
    "camera = 'ACS' #WFC3\n",
    "\n",
    "Lens_List = pd.read_csv((Main_dir/f'{proposal_id_no}_targets.csv'))\n",
    "Processed_Lenses = []\n",
    "for _, row in Lens_List.iterrows():\n",
    "    ra = row['RAJ2000']\n",
    "    dec = row['DECJ2000']\n",
    "    z_src = row['z_spec_SRC_Spectral_Observations_Tally'] if not np.isnan(row['z_spec_SRC_Spectral_Observations_Tally']) else row['z_source (from DR2 Redshifts)'] if not np.isnan(row['z_source (from DR2 Redshifts)']) else row['z_spec_SRC'] if not np.isnan(row['z_spec_SRC']) else None\n",
    "    z_def = row['z_spec_DE_Spectral_Observations_Tally'] if not np.isnan(row['z_spec_DE_Spectral_Observations_Tally']) else row['z_deflector (from DR2 Redshifts)'] if not np.isnan(row['z_deflector (from DR2 Redshifts)']) else row['z_spec_DE'] if not np.isnan(row['z_spec_DE']) else None\n",
    "\n",
    "    if proposal_id_no == '16773':\n",
    "        Processed_Lenses.append([row['objname'], ra, dec, filters, [z_def, z_src], [proposal_id_no, proposal_id_no], [camera,camera]])\n",
    "    else:\n",
    "        Processed_Lenses.append([row['objname'], ra, dec, filters, [z_def, z_src], [proposal_id_no], [camera]])\n",
    "\n",
    "print(f\"Loaded {len(Processed_Lenses)} entries.\")\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9682417",
   "metadata": {},
   "source": [
    "## Run it all\n",
    "\n",
    "If astrodrizzle or tweakreg fails, check your individual exposures to make sure they are actually good\n",
    "\n",
    "Some targets may need to be treated individually by running just AD or tweak on a few exposures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6c1ecd1f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "=== Processing AGEL051603-220847A F606W ACS ===\n",
      "Setting up logfile :  astrodrizzle.log\n",
      "AstroDrizzle log file: astrodrizzle.log\n",
      "AstroDrizzle Version 3.10.0rc2.dev46+g45739e1ff started at: 15:40:15.73 (12/01/2026)\n",
      "\n",
      "\n",
      "==== Processing Step 'Initialization' started at 15:40:15.736 (12/01/2026)\n",
      "Preserving original of:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits as  OrIg_files/jf5453c0q_flc.fits\n",
      "Preserving original of:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits as  OrIg_files/jf5453c1q_flc.fits\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.0323494900064 -22.169576092205777 \n",
      "CRPIX : 2108.5 2120.5 \n",
      "CD1_1 CD1_2  : -1.3844322305856903e-05 1.111743882130348e-06 \n",
      "CD2_1 CD2_2  : 1.111743882130348e-06 1.3844322305856903e-05 \n",
      "NAXIS : 4217  4241\n",
      "********************************************************************************\n",
      "*\n",
      "*  Estimated memory usage:  up to 1074 Mb.\n",
      "*  Output image size:       4217 X 4241 pixels. \n",
      "*  Output image file:       ~ 204 Mb. \n",
      "*  Cores available:         4\n",
      "*\n",
      "********************************************************************************\n",
      "==== Processing Step 'Initialization'' finished at 15:40:16.131 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Static Mask' started at 15:40:16.131 (12/01/2026)\n",
      "==== Processing Step 'Static Mask'' finished at 15:40:16.464 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Subtract Sky' started at 15:40:16.464 (12/01/2026)\n",
      "***** skymatch started on 2026-01-12 15:40:16.538739\n",
      "      Version 1.0.11\n",
      "\n",
      "'skymatch' task will apply computed sky differences to input image file(s).\n",
      "\n",
      "NOTE: Computed sky values WILL NOT be subtracted from image data ('subtractsky'=False).\n",
      "'MDRIZSKY' header keyword will represent sky value *computed* from data.\n",
      "\n",
      "-----  User specified keywords:  -----\n",
      "       Sky Value Keyword:  'MDRIZSKY'\n",
      "       Data Units Keyword: 'BUNIT'\n",
      "\n",
      "\n",
      "-----  Input file list:  -----\n",
      "\n",
      "   **  Input image: 'jf5453c0q_flc.fits'\n",
      "       EXT: 'SCI',1;\tMASK: jf5453c0q_skymatch_mask_sci1.fits[0]\n",
      "       EXT: 'SCI',2;\tMASK: jf5453c0q_skymatch_mask_sci2.fits[0]\n",
      "\n",
      "   **  Input image: 'jf5453c1q_flc.fits'\n",
      "       EXT: 'SCI',1;\tMASK: jf5453c1q_skymatch_mask_sci1.fits[0]\n",
      "       EXT: 'SCI',2;\tMASK: jf5453c1q_skymatch_mask_sci2.fits[0]\n",
      "\n",
      "-----  Sky statistics parameters:  -----\n",
      "       statistics function: 'median'\n",
      "       lower = None\n",
      "       upper = None\n",
      "       nclip = 5\n",
      "       lsigma = 4.0\n",
      "       usigma = 4.0\n",
      "       binwidth = 0.1\n",
      "\n",
      "-----  Data->Brightness conversion parameters for input files:  -----\n",
      "\n",
      "   *   Image: jf5453c0q_flc.fits\n",
      "       EXT = 'SCI',1\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "       EXT = 'SCI',2\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "\n",
      "   *   Image: jf5453c1q_flc.fits\n",
      "       EXT = 'SCI',1\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "       EXT = 'SCI',2\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "\n",
      "\n",
      "-----  Computing sky values requested image extensions (detector chips):  -----\n",
      "\n",
      "   *   Image:   'jf5453c0q_flc.fits['SCI',1,2]'  --  SKY = 27.4925537109375 (brightness units)\n",
      "       Sky change (data units):\n",
      "      - EXT = 'SCI',1   delta(MDRIZSKY) = 23.1625   NEW MDRIZSKY = 23.1625\n",
      "      - EXT = 'SCI',2   delta(MDRIZSKY) = 23.1625   NEW MDRIZSKY = 23.1625\n",
      "   *   Image:   'jf5453c1q_flc.fits['SCI',1,2]'  --  SKY = 26.573368072509766 (brightness units)\n",
      "       Sky change (data units):\n",
      "      - EXT = 'SCI',1   delta(MDRIZSKY) = 22.3881   NEW MDRIZSKY = 22.3881\n",
      "      - EXT = 'SCI',2   delta(MDRIZSKY) = 22.3881   NEW MDRIZSKY = 22.3881\n",
      "***** skymatch ended on 2026-01-12 15:40:17.168412\n",
      "TOTAL RUN TIME: 0:00:00.629673\n",
      "==== Processing Step 'Subtract Sky'' finished at 15:40:17.32 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Separate Drizzle' started at 15:40:17.329 (12/01/2026)\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.0323494900064 -22.169576092205777 \n",
      "CRPIX : 2108.5 2120.5 \n",
      "CD1_1 CD1_2  : -1.3844322305856903e-05 1.111743882130348e-06 \n",
      "CD2_1 CD2_2  : 1.111743882130348e-06 1.3844322305856903e-05 \n",
      "NAXIS : 4217  4241\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_sci.fits\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_sci.fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: VerifyWarning: Card is too long, comment will be truncated. [astropy.io.fits.card]\n",
      "WARNING: VerifyWarning: Card is too long, comment will be truncated. [astropy.io.fits.card]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_wht.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_wht.fits\n",
      "==== Processing Step 'Separate Drizzle'' finished at 15:40:18.531 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Create Median' started at 15:40:18.5 (12/01/2026)\n",
      "reference sky value for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits' is 23.1624755859375\n",
      "reference sky value for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits' is 22.3880615234375\n",
      "Saving output median image to: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_med.fits'\n",
      "==== Processing Step 'Create Median'' finished at 15:40:20.053 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Blot' started at 15:40:20.054 (12/01/2026)\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits[sci,1]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits[sci,2]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits[sci,1]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits[sci,2]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_blt.fits\n",
      "==== Processing Step 'Blot'' finished at 15:40:21.795 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Driz_CR' started at 15:40:21.795 (12/01/2026)\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_crmask.fits\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_crmask.fits\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_crmask.fits\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_crmask.fits\n",
      "Created CR corrected file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits'\n",
      "Created CR corrected file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits'\n",
      "==== Processing Step 'Driz_CR'' finished at 15:40:23.472 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Final Drizzle' started at 15:40:23.477 (12/01/2026)\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.0323494900064 -22.169576092205777 \n",
      "CRPIX : 2108.5 2120.5 \n",
      "CD1_1 CD1_2  : -1.3844322305856903e-05 1.111743882130348e-06 \n",
      "CD2_1 CD2_2  : 1.111743882130348e-06 1.3844322305856903e-05 \n",
      "NAXIS : 4217  4241\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_sci.fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: VerifyWarning: Card is too long, comment will be truncated. [astropy.io.fits.card]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_wht.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_ctx.fits\n",
      "==== Processing Step 'Final Drizzle'' finished at 15:40:26.896 (12/01/2026)\n",
      "\n",
      "AstroDrizzle Version 3.10.0rc2.dev46+g45739e1ff is finished processing at 15:40:26.896 (12/01/2026).\n",
      "\n",
      "\n",
      "\n",
      "   --------------------          --------------------\n",
      "                   Step          Elapsed time\n",
      "   --------------------          --------------------\n",
      "\n",
      "   Initialization                0.3948 sec \n",
      "   Static Mask                   0.3326 sec \n",
      "   Subtract Sky                  0.8637 sec \n",
      "   Separate Drizzle              1.2024 sec \n",
      "   Create Median                 1.5209 sec \n",
      "   Blot                          1.7412 sec \n",
      "   Driz_CR                       1.6766 sec \n",
      "   Final Drizzle                 3.4182 sec \n",
      "   ====================          ====================\n",
      "   Total                         11.1504 sec\n",
      "\n",
      "Trailer file written to:  astrodrizzle.log\n",
      "Setting up logfile :  tweakreg.log\n",
      "TweakReg Version 3.10.0rc2.dev46+g45739e1ff started at: 15:40:26.928 (12/01/2026) \n",
      "\n",
      "Version Information\n",
      "--------------------\n",
      "Python Version 3.12.10 | packaged by conda-forge | (main, Apr 10 2025, 22:19:24) [Clang 18.1.8 ]\n",
      "numpy Version -> 2.2.5 \n",
      "astropy Version -> 7.0.1 \n",
      "stwcs Version -> 1.7.4 \n",
      "photutils Version -> 2.2.0 \n",
      "\n",
      "Finding shifts for: \n",
      "    /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits\n",
      "    /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits\n",
      "\n",
      "===  Source finding for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits':\n",
      "  #  Source finding for '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits', EXT=('SCI', 1) started at: 15:40:27.007 (12/01/2026)\n",
      "     Found 595 objects.\n",
      "  #  Source finding for '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits', EXT=('SCI', 2) started at: 15:40:27.181 (12/01/2026)\n",
      "     Found 573 objects.\n",
      "===  FINAL number of objects in image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits': 1168\n",
      "\n",
      "===  Source finding for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits':\n",
      "  #  Source finding for '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits', EXT=('SCI', 1) started at: 15:40:27.527 (12/01/2026)\n",
      "     Found 622 objects.\n",
      "  #  Source finding for '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits', EXT=('SCI', 2) started at: 15:40:27.702 (12/01/2026)\n",
      "     Found 587 objects.\n",
      "===  FINAL number of objects in image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits': 1209\n",
      "\n",
      "\n",
      "===============================================================\n",
      "Performing alignment in the projection plane defined by the WCS\n",
      "derived from '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits'\n",
      "===============================================================\n",
      "\n",
      "\n",
      "====================\n",
      "Performing fit for: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits\n",
      "\n",
      "Matching sources from '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits' with sources from reference image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits'\n",
      "Computing initial guess for X and Y shifts...\n",
      "Found initial X and Y shifts of -0.1872, 0.194 with significance of 918.8 and 1047 matches\n",
      "Found 1002 matches for /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits...\n",
      "Computed  rscale  fit for  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits : \n",
      "XSH: 0.0022  YSH: 0.0025    ROT: 359.9996746    SCALE: 1.000005\n",
      "FIT XRMS: 0.13       FIT YRMS: 0.077  \n",
      "FIT RMSE: 0.15       FIT MAE: 0.13   \n",
      "\n",
      "RMS_RA: 1.8e-06 (deg)   RMS_DEC: 1.2e-06 (deg)\n",
      "\n",
      "Final solution based on  944  objects.\n",
      "wrote XY data to:  jf5453c1q_crclean_catalog_fit.match\n",
      "Total # points: 944\n",
      "# of points after clipping: 944\n",
      "Total # points: 944\n",
      "# of points after clipping: 944\n",
      "\n",
      "....Updating header for '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits' ...\n",
      "\n",
      "\n",
      "Processing /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits['SCI',1]\n",
      "\n",
      "Updating header for /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits[1]\n",
      "WCS Keywords\n",
      "\n",
      "CD_11  CD_12: np.float64(-1.3758009655214056e-05) np.float64(5.73389966712059e-07)\n",
      "CD_21  CD_22: np.float64(1.5254345209518136e-06) np.float64(1.396211018701199e-05)\n",
      "CRVAL    : np.float64(79.03202673468117) np.float64(-22.183901144973426)\n",
      "CRPIX    : np.float64(2048.0) np.float64(1024.0)\n",
      "NAXIS    : 4096 2048\n",
      "Plate Scale : np.float64(0.04983259701270116)\n",
      "ORIENTAT : np.float64(2.351677079883593)\n",
      "WCSNAME  :  UVIS_FLC\n",
      "\n",
      "Processing /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits['SCI',2]\n",
      "\n",
      "Updating header for /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_crclean.fits[4]\n",
      "WCS Keywords\n",
      "\n",
      "CD_11  CD_12: np.float64(-1.3575931496793317e-05) np.float64(4.512116257973277e-07)\n",
      "CD_21  CD_22: np.float64(1.69006899512701e-06) np.float64(1.350032164662288e-05)\n",
      "CRVAL    : np.float64(79.03324134790596) np.float64(-22.155043016293046)\n",
      "CRPIX    : np.float64(2048.0) np.float64(1024.0)\n",
      "NAXIS    : 4096 2048\n",
      "Plate Scale : np.float64(0.04925085932325769)\n",
      "ORIENTAT : np.float64(1.9142434356925377)\n",
      "WCSNAME  :  UVIS_FLC\n",
      "\n",
      "Processing /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits['SCI',1]\n",
      "\n",
      "Updating header for /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits[('SCI', 1)]\n",
      "WCS Keywords\n",
      "\n",
      "CD_11  CD_12: np.float64(-1.3758107586858e-05) np.float64(5.7310879805515e-07)\n",
      "CD_21  CD_22: np.float64(1.5251531245907e-06) np.float64(1.3962240090432e-05)\n",
      "CRVAL    : np.float64(79.031954077302) np.float64(-22.183872706838)\n",
      "CRPIX    : np.float64(2048.0) np.float64(1024.0)\n",
      "NAXIS    : 4096 2048\n",
      "Plate Scale : np.float64(0.04983258521156723)\n",
      "ORIENTAT : np.float64(2.3505033559798103)\n",
      "WCSNAME  :  UVIS_FLC\n",
      "\n",
      "Processing /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits['SCI',2]\n",
      "\n",
      "Updating header for /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_crclean.fits[('SCI', 2)]\n",
      "WCS Keywords\n",
      "\n",
      "CD_11  CD_12: np.float64(-1.3576031893318e-05) np.float64(4.5093931695008e-07)\n",
      "CD_21  CD_22: np.float64(1.6897929123228e-06) np.float64(1.3500445003501e-05)\n",
      "CRVAL    : np.float64(79.033168062503) np.float64(-22.155014310966)\n",
      "CRPIX    : np.float64(2048.0) np.float64(1024.0)\n",
      "NAXIS    : 4096 2048\n",
      "Plate Scale : np.float64(0.04925084755648185)\n",
      "ORIENTAT : np.float64(1.9130715699523133)\n",
      "WCSNAME  :  UVIS_FLC\n",
      "Writing out shiftfile : /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/shiftuv_flt.txt\n",
      "Trailer file written to:  tweakreg.log\n",
      "TweakBack Version 3.10.0rc2.dev46+g45739e1ff started at: 15:40:28.936 (12/01/2026)\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: AstropyDeprecationWarning: The tweakback function is deprecated and may be removed in a future version.\n",
      "        Use apply_tweak instead. [warnings]\n",
      "WARNING: AstropyDeprecationWarning: The tweakback function is deprecated and may be removed in a future version.\n",
      "        Use apply_tweak instead. [warnings]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TweakBack Version 3.10.0rc2.dev46+g45739e1ff started at: 15:40:29.253 (12/01/2026)\n",
      "\n",
      "Setting up logfile :  astrodrizzle.log\n",
      "AstroDrizzle log file: astrodrizzle.log\n",
      "AstroDrizzle Version 3.10.0rc2.dev46+g45739e1ff started at: 15:40:29.540 (12/01/2026)\n",
      "\n",
      "\n",
      "==== Processing Step 'Initialization' started at 15:40:29.542 (12/01/2026)\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.03236967542509 -22.169557943923582 \n",
      "CRPIX : 2108.0 2120.5 \n",
      "CD1_1 CD1_2  : -1.384432230644147e-05 1.1117438748508325e-06 \n",
      "CD2_1 CD2_2  : 1.1117438748508325e-06 1.384432230644147e-05 \n",
      "NAXIS : 4216  4241\n",
      "********************************************************************************\n",
      "*\n",
      "*  Estimated memory usage:  up to 1074 Mb.\n",
      "*  Output image size:       4216 X 4241 pixels. \n",
      "*  Output image file:       ~ 204 Mb. \n",
      "*  Cores available:         4\n",
      "*\n",
      "********************************************************************************\n",
      "==== Processing Step 'Initialization'' finished at 15:40:29.847 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Static Mask' started at 15:40:29.848 (12/01/2026)\n",
      "==== Processing Step 'Static Mask'' finished at 15:40:30.131 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Subtract Sky' started at 15:40:30.131 (12/01/2026)\n",
      "***** skymatch started on 2026-01-12 15:40:30.199745\n",
      "      Version 1.0.11\n",
      "\n",
      "'skymatch' task will apply computed sky differences to input image file(s).\n",
      "\n",
      "NOTE: Computed sky values WILL NOT be subtracted from image data ('subtractsky'=False).\n",
      "'MDRIZSKY' header keyword will represent sky value *computed* from data.\n",
      "\n",
      "-----  User specified keywords:  -----\n",
      "       Sky Value Keyword:  'MDRIZSKY'\n",
      "       Data Units Keyword: 'BUNIT'\n",
      "\n",
      "\n",
      "-----  Input file list:  -----\n",
      "\n",
      "   **  Input image: 'jf5453c0q_flc.fits'\n",
      "       EXT: 'SCI',1;\tMASK: jf5453c0q_skymatch_mask_sci1.fits[0]\n",
      "       EXT: 'SCI',2;\tMASK: jf5453c0q_skymatch_mask_sci2.fits[0]\n",
      "\n",
      "   **  Input image: 'jf5453c1q_flc.fits'\n",
      "       EXT: 'SCI',1;\tMASK: jf5453c1q_skymatch_mask_sci1.fits[0]\n",
      "       EXT: 'SCI',2;\tMASK: jf5453c1q_skymatch_mask_sci2.fits[0]\n",
      "\n",
      "-----  Sky statistics parameters:  -----\n",
      "       statistics function: 'median'\n",
      "       lower = None\n",
      "       upper = None\n",
      "       nclip = 5\n",
      "       lsigma = 4.0\n",
      "       usigma = 4.0\n",
      "       binwidth = 0.1\n",
      "\n",
      "-----  Data->Brightness conversion parameters for input files:  -----\n",
      "\n",
      "   *   Image: jf5453c0q_flc.fits\n",
      "       EXT = 'SCI',1\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "       EXT = 'SCI',2\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "\n",
      "   *   Image: jf5453c1q_flc.fits\n",
      "       EXT = 'SCI',1\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "       EXT = 'SCI',2\n",
      "             Data units type: COUNTS\n",
      "             EXPTIME: 337.0 [s]\n",
      "             Conversion factor (data->brightness):  1.1869436201780414\n",
      "\n",
      "\n",
      "-----  Computing sky values requested image extensions (detector chips):  -----\n",
      "\n",
      "   *   Image:   'jf5453c0q_flc.fits['SCI',1,2]'  --  SKY = 27.458688735961914 (brightness units)\n",
      "       Sky change (data units):\n",
      "      - EXT = 'SCI',1   delta(MDRIZSKY) = 23.1339   NEW MDRIZSKY = 23.1339\n",
      "      - EXT = 'SCI',2   delta(MDRIZSKY) = 23.1339   NEW MDRIZSKY = 23.1339\n",
      "   *   Image:   'jf5453c1q_flc.fits['SCI',1,2]'  --  SKY = 26.549463272094727 (brightness units)\n",
      "       Sky change (data units):\n",
      "      - EXT = 'SCI',1   delta(MDRIZSKY) = 22.3679   NEW MDRIZSKY = 22.3679\n",
      "      - EXT = 'SCI',2   delta(MDRIZSKY) = 22.3679   NEW MDRIZSKY = 22.3679\n",
      "***** skymatch ended on 2026-01-12 15:40:30.773713\n",
      "TOTAL RUN TIME: 0:00:00.573968\n",
      "==== Processing Step 'Subtract Sky'' finished at 15:40:30.934 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Separate Drizzle' started at 15:40:30.934 (12/01/2026)\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.03236967542509 -22.169557943923582 \n",
      "CRPIX : 2108.0 2120.5 \n",
      "CD1_1 CD1_2  : -1.384432230644147e-05 1.1117438748508325e-06 \n",
      "CD2_1 CD2_2  : 1.1117438748508325e-06 1.384432230644147e-05 \n",
      "NAXIS : 4216  4241\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_sci.fits\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_single_wht.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_single_wht.fits\n",
      "==== Processing Step 'Separate Drizzle'' finished at 15:40:32.125 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Create Median' started at 15:40:32.126 (12/01/2026)\n",
      "reference sky value for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits' is 23.13394546508789\n",
      "reference sky value for image '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits' is 22.367921829223633\n",
      "Saving output median image to: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_med.fits'\n",
      "==== Processing Step 'Create Median'' finished at 15:40:33.580 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Blot' started at 15:40:33.580 (12/01/2026)\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits[sci,1]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_flc.fits[sci,2]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits[sci,1]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_blt.fits\n",
      "    Blot: creating blotted image:  /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_flc.fits[sci,2]\n",
      "Using default C-based coordinate transformation...\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_blt.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_blt.fits\n",
      "==== Processing Step 'Blot'' finished at 15:40:35.366 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Driz_CR' started at 15:40:35.367 (12/01/2026)\n",
      "Removed old cosmic ray mask file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_crmask.fits'\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci1_crmask.fits\n",
      "Removed old cosmic ray mask file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_crmask.fits'\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci1_crmask.fits\n",
      "Removed old cosmic ray mask file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_crmask.fits'\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c1q_sci2_crmask.fits\n",
      "Removed old cosmic ray mask file: '/Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_crmask.fits'\n",
      "Creating output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp/jf5453c0q_sci2_crmask.fits\n",
      "==== Processing Step 'Driz_CR'' finished at 15:40:36.606 (12/01/2026)\n",
      "\n",
      "==== Processing Step 'Final Drizzle' started at 15:40:36.611 (12/01/2026)\n",
      "WCS Keywords\n",
      "\n",
      "Number of WCS axes: 2\n",
      "CTYPE : 'RA---TAN' 'DEC--TAN' \n",
      "CRVAL : 79.03236967542509 -22.169557943923582 \n",
      "CRPIX : 2108.0 2120.5 \n",
      "CD1_1 CD1_2  : -1.384432230644147e-05 1.1117438748508325e-06 \n",
      "CD2_1 CD2_2  : 1.1117438748508325e-06 1.384432230644147e-05 \n",
      "NAXIS : 4216  4241\n",
      "-Generating simple FITS output: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_sci.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_wht.fits\n",
      "Writing out image to disk: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/AGEL051603-220847A_F606W_ACS_drc_ctx.fits\n",
      "==== Processing Step 'Final Drizzle'' finished at 15:40:40.163 (12/01/2026)\n",
      "\n",
      "AstroDrizzle Version 3.10.0rc2.dev46+g45739e1ff is finished processing at 15:40:40.163 (12/01/2026).\n",
      "\n",
      "\n",
      "\n",
      "   --------------------          --------------------\n",
      "                   Step          Elapsed time\n",
      "   --------------------          --------------------\n",
      "\n",
      "   Initialization                0.3051 sec \n",
      "   Static Mask                   0.2831 sec \n",
      "   Subtract Sky                  0.8028 sec \n",
      "   Separate Drizzle              1.1903 sec \n",
      "   Create Median                 1.4538 sec \n",
      "   Blot                          1.7861 sec \n",
      "   Driz_CR                       1.2391 sec \n",
      "   Final Drizzle                 3.5520 sec \n",
      "   ====================          ====================\n",
      "   Total                         10.6124 sec\n",
      "\n",
      "Trailer file written to:  astrodrizzle.log\n",
      "[CLEAN] Removed temp: /Volumes/AGEL/HST_data/AGEL051603-220847A/HST/17307_F606W/temp\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# --- Run ---\n",
    "count = 0\n",
    "for i in Processed_Lenses:\n",
    "    target = i[0]\n",
    "    ra = i[1]\n",
    "    dec = i[2]\n",
    "    zs_list = i[4]\n",
    "    propids_list = i[5]\n",
    "    filts_list = i[3]\n",
    "    camlist = i[6]\n",
    "\n",
    "    if target[-1] == 'B':\n",
    "        count += 1\n",
    "        continue  # skip B images for now\n",
    "\n",
    "    # if target == 'AGEL051603-220847A':\n",
    "\n",
    "    for i in range(len(filts_list)):\n",
    "        print(f\"\\n=== Processing {target} {filts_list[i]} {camlist[i]} ===\")\n",
    "        if filts_list[i] == 'F140W':\n",
    "            # IR_Drizzler(target, propids_list[i], filts_list[i], camlist[i], 0.08)\n",
    "            continue\n",
    "        else:\n",
    "            UV_Drizzle(target, propids_list[i], filts_list[i], camlist[i], 0.05)\n",
    "    count += 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "032dcf73",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 362 junk files.\n"
     ]
    }
   ],
   "source": [
    "## Extra clean-up of ancillary files\n",
    "DRY_RUN = False  # set False to actually delete\n",
    "\n",
    "targets = []\n",
    "for p in Main_dir.rglob(\"*\"):\n",
    "    if p.is_file() and (p.name.startswith(\"._\") or p.name == \".DS_Store\"):\n",
    "        targets.append(p)\n",
    "\n",
    "print(f\"Found {len(targets)} junk files.\")\n",
    "for t in targets:\n",
    "    if DRY_RUN:\n",
    "        print(\"[DRY-RUN] delete\", t)\n",
    "    else:\n",
    "        try:\n",
    "            t.unlink()\n",
    "        except Exception as e:\n",
    "            print(\"FAILED to delete\", t, \"->\", e)\n",
    "\n",
    "# Optional: remove empty directories after deletion\n",
    "if not DRY_RUN:\n",
    "    empties = [d for d in Main_dir.rglob(\"*\") if d.is_dir() and not any(d.iterdir())]\n",
    "    for d in sorted(empties, key=len, reverse=True):\n",
    "        try:\n",
    "            d.rmdir()\n",
    "        except Exception:\n",
    "            pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "52974d62",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "stenv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
